The influence of behavioral relevance on the processing of global scene properties: An ERP study

Hansen, Natalie; Noesen, Birken; Nador, Jeffrey; Harel, Assaf

doi:10.1016/j.neuropsychologia.2018.04.040

Cited by 18 publications

(34 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1). Therefore, we have refrained from strongly interpreting results for that model, particularly the observation that this feature was not significantly predictive of the behavioral RDM (Table 1) given previous reports that gist features can strongly influence categorization behavior (Greene and Oliva, 2009), vERPs (Hansen et al, 2018), MEG patterns (Ramkumar et al, 2016), and fMRI activation patterns (Watson et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization

Greene

Hansen

2020

J. Neurosci.

View full text Add to dashboard Cite

Human scene categorization is characterized by its remarkable speed. While many visual and conceptual features have been linked to this ability, significant correlations exist between feature spaces, impeding our ability to determine their relative contributions to scene categorization. Here, we used a whitening transformation to decorrelate a variety of visual and conceptual features and assess the time course of their unique contributions to scene categorization. Participants (both sexes) viewed 2250 full-color scene images drawn from 30 different scene categories while having their brain activity measured through 256-channel EEG. We examined the variance explained at each electrode and time point of visual event-related potential (vERP) data from nine different whitened encoding models. These ranged from low-level features obtained from filter outputs to high-level conceptual features requiring human annotation. The amount of category information in the vERPs was assessed through multivariate decoding methods. Behavioral similarity measures were obtained in separate crowdsourced experiments. We found that all nine models together contributed 78% of the variance of human scene similarity assessments and were within the noise ceiling of the vERP data. Low-level models explained earlier vERP variability (88 ms after image onset), whereas high-level models explained later variance (169 ms). Critically, only high-level models shared vERP variability with behavior. Together, these results suggest that scene categorization is primarily a high-level process, but reliant on previously extracted low-level features.

show abstract

Section: Discussionmentioning

confidence: 99%

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization

Greene

Hansen

2020

J. Neurosci.

View full text Add to dashboard Cite

show abstract

“…However, there are a growing number of behavioral studies showing the necessity of attention for certain cognitive processes in scene perception (Potter and Fox 2009; Cohen et al 2011). While the debate about the role of attention in scene perception is highly topical in behavioral research (Gronau and Izoutcheev 2017; Hansen et al 2018), the fMRI research still predominantly employs a passive paradigm which presumably relies on automatic activation.…”

Section: Introductionmentioning

confidence: 99%

Parsing rooms: the role of the PPA and RSC in perceiving object relations and spatial layout

2019

View full text Add to dashboard Cite

The perception of a scene involves grasping the global space of the scene, usually called the spatial layout, as well as the objects in the scene and the relations between them. The main brain areas involved in scene perception, the parahippocampal place area (PPA) and retrosplenial cortex (RSC), are supposed to mostly support the processing of spatial layout. Here we manipulated the objects and their relations either by arranging objects within rooms in a common way or by scattering them randomly. The rooms were then varied for spatial layout by keeping or removing the walls of the room, a typical layout manipulation. We then combined a visual search paradigm, where participants actively search for an object within the room, with multivariate pattern analysis (MVPA). Both left and right PPA were sensitive to the layout properties, but the right PPA was also sensitive to the object relations even when the information about objects and their relations is used in the cross-categorization procedure on novel stimuli. The left and right RSC were sensitive to both spatial layout and object relations, but could only use the information about object relations for cross-categorization to novel stimuli. These effects were restricted to the PPA and RSC, as other control brain areas did not display the same pattern of results. Our results underline the importance of employing paradigms that require participants to explicitly retrieve domain-specific processes and indicate that objects and their relations are processed in the scene areas to a larger extent than previously assumed.

show abstract

“…While the P2 has previously been advanced as a marker for scene processing (Harel et al, 2016), there is debate as to whether this component is sensitive to top-down influence. For example, recent research found no top-down modulatory effect (Hansen et al, 2018), at least in relation to observer-based goals. Conversely, some forms of early higher-order influence have been implied, as changes to amplitude at ∼200 ms post-stimulus have been observed with tasks involving the detection of objects within natural scenes, potentially reflecting decision-related activation (Thorpe et al, 1996; VanRullen & Thorpe, 2001), and tasks that manipulated the emotional nature of scene-images, argued as being driven by motivational systems (Schupp et al, 2006).…”

Section: Discussionmentioning

confidence: 98%

“…Therefore, the first ERP component selected for investigation was the P2. Arising rapidly within Parieto-occipital regions – at around 200 ms after target onset – this component has been proposed as the earliest known marker for scene-specific processing (Harel et al, 2016), affected by changes in global scene properties but not top-down observer-based goals (Hansen et al, 2018). However, the exact influence of top-down information on the P2 remains unclear.…”

Section: Methodsmentioning

confidence: 99%

“…A Centro-parietal ROI included electrodes C1/C2, C3/C4, CP1/CP2 and CP3/CP4, a Parieto-occipital ROI comprised electrodes P1/P2, P3/P4, P5/P6 and PO3/PO4, and a Frontal ROI contained electrodes F1/F2, F3/F4, F5/F6, and AF3/AF4 (see Figure 9). The posterior ROI was selected as Parieto-occipital regions are associated with maximal amplitude of the P600 (e.g., Gouvea et al, 2010) and the P2 (e.g., Hansen et al, 2018). The more central and anterior ROIs were chosen as the amplitude of the N400 has previously been found to be maximal at Centro-parietal regions (e.g., Ganis & Kutas, 2003), while the processing of semantic information related to images, as compared to text, has often been shown to elicit a Frontal negativity during the 300-500 ms temporal window (e.g., Ganis et al, 1996; Holcomb & McPherson, 1994; Mudrik et al, 2014).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Expectation-Based Gist Facilitation: Rapid Scene Understanding and the Role of Top-Down Information

McLean

Renoult

Malcolm

2021

Preprint

View full text Add to dashboard Cite

Scene meaning is processed rapidly, with 'gist' extracted even when presentation duration spans a few dozen milliseconds. This has led some to suggest a primacy of bottom-up information. However, gist research has typically relied on showing successions of unrelated scene images, contrary to our everyday experience in which the world unfolds around us in a predictable manner. Thus, we investigated whether top-down information - in the form of observers' predictions of an upcoming scene - facilitates gist processing. Within each trial, participants (N=336) experienced a series of images, organised to represent an approach to a destination (e.g., walking down a sidewalk), followed by a final target scene either congruous or incongruous with the expected destination (e.g., a store interior or a bedroom). Over a series of behavioural experiments, we found that: appropriate expectations facilitated gist processing; inappropriate expectations interfered with gist processing; the effect of congruency was driven by provision of contextual information rather than the thematic coherence of approach images, and; expectation-based facilitation was most apparent when destination duration was most curtailed. We then investigated the neural correlates of predictability on scene processing using ERP (N=26). Congruency-related differences were found in a putative scene-selective ERP component, related to integrating visual properties (P2), and in later components related to contextual integration including semantic and syntactic coherence (N400 and P600, respectively). Taken together, these results suggest that in real-world situations, top-down predictions of an upcoming scene influence even the earliest stages of its processing, affecting both the integration of visual properties and meaning. Keywords: scene processing, gist, top-down information, event-related potentials, semantic integration

show abstract

The influence of behavioral relevance on the processing of global scene properties: An ERP study

Cited by 18 publications

References 75 publications

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization

Parsing rooms: the role of the PPA and RSC in perceiving object relations and spatial layout

Expectation-Based Gist Facilitation: Rapid Scene Understanding and the Role of Top-Down Information

Contact Info

Product

Resources

About